Combinatorial Analysis of Circulating Biomarkers and Maternal Characteristics for Preeclampsia Prediction in the First and Third Trimesters in Asia

Willie Lin, Sen Wen Teng, Tzu Yi Lin, Ronald Lovel, Hsin Yu Sung, Wen Ying Chang, Tang Bo Chung Wu, Hsuan Yu Chen, Le Ming Wang, Steven W. Shaw

研究成果: 雜誌貢獻文章同行評審

摘要

We aim to establish a prediction model for pregnancy outcomes through a combinatorial analysis of circulating biomarkers and maternal characteristics to effectively identify pregnant women with higher risks of preeclampsia in the first and third trimesters within the Asian population. A total of two hundred and twelve pregnant women were screened for preeclampsia through a multicenter study conducted in four recruiting centers in Taiwan from 2017 to 2020. In addition, serum levels of sFlt-1/PlGF ratio, miR-181a, miR-210 and miR-223 were measured and transformed into multiples of the median. We thus further developed statistically validated algorithmic models by designing combinations of different maternal characteristics and biomarker levels. Through the performance of the training cohort (0.848 AUC, 0.73–0.96 95% CI, 80% sensitivity, 85% specificity, p < 0.001) and the validation cohort (0.852 AUC, 0.74–0.98 95% CI, 75% sensitivity, 87% specificity, p < 0.001) from one hundred and fifty-two women with a combination of miR-210, miR-181a and BMI, we established a preeclampsia prediction model for the first trimester. We successfully identified pregnant women with higher risks of preeclampsia in the first and third trimesters in the Asian population using the established prediction models that utilized combinatorial analysis of circulating biomarkers and maternal characteristics.

原文英語
文章編號1533
期刊Diagnostics
12
發行號7
DOIs
出版狀態已發佈 - 7月 2022

ASJC Scopus subject areas

  • 臨床生物化學

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